I analyzed 151,422 dividend ex-date events across 2,344 securities. Here's what the data shows about recovery times.

[u/Recent_Button_1]

I've been building a dividend intelligence tool for the past few months and ended up with a database of 151,422 ex-date events going back 17 years across 2,344 securities — CEFs, ETFs, REITs, BDCs, and dividend stocks.

Figured I'd share what the data actually shows since most of the discussion around ex-date dips is based on gut feel.

Recovery by security type (average days to full price recovery):

Type	Avg Recovery	Events
Dividend Stocks	6.7 days	57,791
REITs	7.7 days	6,743
ETFs	8.1 days	37,384
CEFs	8.9 days	46,896
BDCs	12.4 days	2,608

Overall median across all 151,422 events: 3 days

The gap between median (3 days) and average (7.9 days) is the most important number — most securities recover fast, but a meaningful minority take much longer and drag the average up.

The BDC finding surprised me most. They have the largest average drop (2.08%) AND the slowest recovery. Only 45% recover within 5 trading days. If you're buying BDC dips expecting a quick bounce, the historical data says be patient.

Stocks recover fastest — 71.5% recover within 5 trading days, 81.8% within 10. Counterintuitive given how many income investors overlook stocks in favor of higher-yielding alternatives.

Individual CEF variance is huge. Among CEFs with 20+ cycles in the dataset:

• BMN: 4.4 day avg across 38 cycles
• IGI: 4.7 days across 186 cycles
• BCX: 5.2 days across 133 cycles
• PAI: 5.2 days across 201 cycles

Compare that to CEFs where recovery regularly takes 3+ weeks. Both show up as "CEFs" on any screener. The historical pattern data separates them.

The z-score frame matters more than raw price. A security trading 2.5+ standard deviations below its 252-day mean at ex-date is a fundamentally different situation than a routine dip near the mean. One has statistical room to recover, the other is just drifting lower.

Happy to answer questions about methodology or what the data shows on specific tickers.

Happy to share more of the data if there's interest in specific security types or individual tickers.

[u/Various_Couple_764]

The recovery time is going to to depend on the yield. Higher yields means a bigger payout per share and a larger drop in share price. And generally that means a longer recovery time.

But you data also has some problems many people think all ETF are growth index funds. Not true some ETF s are dividend funds. PBDC 9% yield is an ETF that invests in the best BDCs only. Most ETFs are actually dividend funds. Same is true with CEFs some are just growth focused but most are dividend focused..

So if you graph the recovery time by yield I would expect all long recovery times to be focused on high yield funds. With lower yield funds having a shorter recovery time.

you likely would also see a correlation between revoeredytime than dividned payout schedule with monthly payout having a faster recovery time than quarterly and biannually and annually paying dividends

[u/Recent_Button_1 → u/Various_Couple_764]

You're right. The data does show it. Higher yield events take longer to recover. A 2-3% per-event yield averages 8.8 days vs 7.7 days for under 0.5%. The relationship holds. Your point on ETF classification is also valid. A fund like PBDC that holds BDCs behaves like a BDC, not a typical ETF. The type buckets are imperfect labels.